Marc Finzi
14 papers · 2019–2024 · 3 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (39) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Topic Pioneer
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Renaissance Researcher
(5)
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Trend Setter
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Keyword Collector
(75)
Venues
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory Β· Machine Learning
(9)
Deep Learning
(8)
Core Methods
(6)
Artificial Intelligence
(5)
Architectures
(5)
Learning Types Β· Machine Learning
(5)
Core AI
(4)
Application Areas
(3)
Optimization & Theory Β· Deep Learning
(3)
Natural Language Processing
(2)
Learning Types Β· Deep Learning
(2)
Techniques
(2)
Computer Vision
(1)
Mathematics & Optimization
(1)
Keywords
neural network
(4)
representation learning
(2)
large language model
(2)
semi-supervised learning
(2)
image classification
(2)
convolutional neural network
(2)
generalization bound
(2)
gaussian process
(2)
trajectory prediction
(1)
data augmentation
(1)
generative modeling
(1)
model architecture
(1)
transfer learning
(1)
group theory
(1)
image generation
(1)
neural network compression
(1)
automatic differentiation
(1)
constrained optimization
(1)
efficient computing
(1)
neural network optimization
(1)
Papers
Diffusing Differentiable Representations
NeurIPS 2024
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
NeurIPS 2024
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
NeurIPS 2024
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
NeurIPS 2023
Large Language Models Are Zero-Shot Time Series Forecasters
NeurIPS 2023
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
NeurIPS 2022
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
ICML 2021
Residual Pathway Priors for Soft Equivariance Constraints
NeurIPS 2021
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes
ICML 2021
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
ICML 2020
Learning Invariances in Neural Networks from Training Data
NeurIPS 2020
Semi-Supervised Learning with Normalizing Flows
ICML 2020
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
NeurIPS 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
ICLR 2019